COVID19, Government of India, Health, India

Review: What does the RBI report say about COVID-19 impact on States?


The RBI in its annual ‘Study of State Budgets’ report for 2020 dedicated a chapter on the impact of COVID-19 on states. Among other things, the report spoke about the preparedness of states, varied impact in terms of employment, and migration. Here is a review.

In the earlier story, we looked at RBI’s assessment on the impact & spatial dimensions of COVID-19 in various states  as per its ‘Study of State Budgets’ report 2020. RBI observes that a lesser share of old age population (60+), higher per capita GSDP, better government spending on health care has variedly befitted few of the states in handling COVID-19 situation. 

In this story, we look at the other factors which influenced the spread of COVID-19 in India across the states and also ascertain what RBI’s assessment has to say about the impact of COVID-19 on different areas – employment, businesses, financial transactions etc. 

Prevalence of Co-morbidities and Health Infrastructure influenced COVID-19 handling

As per the information by WHO and other medical agencies, apart from older people , people suffering from other risk conditions (co-morbidities) including – respiratory illness, cardiovascular diseases, diabetes etc. carry a higher risk of developing COVID-19 related serious illness.

The lower fatality rate in India can be attributed to the relatively lesser share of old age population  and the population suffering from these risk conditions compared to other countries. 

However there exists significant differences between the various states. Most of the higher income states also have a higher share of the population suffering from ailments that are linked to COVID-19 co-morbidities. In contrast, the lesser income states have a lesser share of population who suffer from such ailments. It ought to be noted that the pattern of the states regarding the prevalence of these risk-conditions is similar to the pattern observed regarding the share of old-age (60+) populations. This is an additional factor influencing the prevalence of COVID-19 infection as well as the strategies developed by the states to handle the situation. 

While the presence of high-risk population contributed to a greater  number of COVID-19 cases as seen in Maharashtra, Delhi, Andhra Pradesh, Tamil Nadu etc., the Case Fatality Rate (CFR) is comparably lower in most of these states. This can be attributed to the availability of better health infrastructure (public as well as private) in these states. Most of these states with lower CFR despite a high number of cases are those who have reported a higher healthcare spending and higher out of pocket expenditure. 

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Kerala, which has the highest share of old age population along with higher share of population with risk conditions, has managed to keep COVID-19 infection to moderate levels with a very low CFR. This can be attributed to the higher healthcare spending (both the government spending and out of pocket expenditure) creating access to better healthcare. The same has also helped the state with effective handling of Nipah Virus earlier. 

While the lower income states like U.P, Bihar, Jharkhand etc. managed to have lower rates of COVID-19 infection, largely thanks to their younger and less health risk prone population, the lesser public spending on health can pose a potential risk for future. With migrant population returning to these states increases the scope for a new wave of COVID-19 infections. 

Higher proportion of reverse migration happened into Bihar, UP & Odisha. 

The RBI refers to ILO’s (International Labour Organization)  report that around 40 crores workers in the informal sector are at the risk of falling deeper into financial scarcity. It observes that COVID-19 situation has resulted in large scale migration as a result of job losses post lockdown. This has prompted the migrant labourers to go back to their native places and also had an effect on the labour shortages in the places they had left. The push factors which have caused the reverse migration due to COVID-19 include – loss of employment, lower earnings, limited access to social unemployment benefits, uncertainty etc. 

A sizeable portion of India’s workforce consists of inter-state migrants. Census data shows that the overall migrant population (including migrant labourers) increased from 41.1 million in 2001 to 54.2 million in 2011. Apart from interstate migrants, there are also intra state migrants (between districts, within districts etc.), with the overall migrant workforce estimated to be around 450 million in 2011. 

The flow of these migrants is majorly out of UP, Bihar, Rajasthan & Odisha and into Maharashtra, Delhi, Gujarat, West Bengal etc. 

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COVID-19 has resulted in a switch of the inflow & outflow states. This is corroborated by the information on the number of travellers on Shramik trains. Highest number of migrants travelled back to UP, Bihar, Odisha, West Bengal etc. from Gujarat, Maharashtra, Tamil Nadu, Rajasthan etc. 

This has an impact on the trends over many years regarding the flow of migrant population among the states, creating a scenario where in: 

  • there is lack of workers in labour inflow states as the migrant workers have left. 
  • an increased demand for work in out flow states like UP & Bihar to where the migrants have returned to. 
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Lack of employment has resulted in increase of work demand under MGNREGA 

As per Centre for Monitoring Indian Economy (CMIE)’s data, there has been a sharp increase in the unemployment during April-May 2020 i.e. during the lock down  period. The unemployment rate was back to pre-lockdown levels post lockdown i.e. with a gradual improvement during the different unlock phases. This also corresponds to the return to pre-lockdown levels of labour force participation rate. 

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While this is a positive trend, the nature of employment being generated post lockdown has to be analysed carefully. MGNREGA data shows an increase in the demand for employment during May-June’2020 compared to same period in previous years. This clearly means loss of current employment and therefore the reliance on government to provide employment. 

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The loss of jobs can also be understood from the fact that the states which are major employers through MSMEs (Medium, Small & Micro Enterprises) are also the states which are majorly hit by COVID-19. The lockdown measures and the other factors in these states could have had an impact on the employment, further triggering the reverse migration.  

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Large disparity among states regarding digital preparedness 

One of the aspects which came to fore due to the COVID-19 related social distancing norms is the reliance on digital technology. The data relating to ‘Digital Preparedness of the States -2020’ shows the disparity that exists among the states. 

States like UP, Bihar along with few of the North-Eastern states are below the national average in terms access to Banking facilities. This becomes crucial for the governments to transfer the benefits of various schemes & initiatives especially during a pandemic situation like COVID-19. The lack of digital preparedness creates a situation where in the beneficiaries in respective states are not able to take advantage of the assistance being extended by the governments. When correlated with the extent of migrants who have returned to these states and require assistance, the problems are compounded. 

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Apart from the benefits that can be leveraged through the Direct Benefit Transfers (DBT) by the government, another aspect of digital preparedness that comes in handy during situations like COVID-19 is the role financial and business transactions. 

Digital Payments have created a scope for businesses to restart and continue their business during the pandemic in view of the social distancing norms. The data provided by National Payments Corporation of India, shows disparity among states with respect to the change in usage of digital transactions during the lockdown period i.e. Q1: 2020-21. Few of the states were unable to facilitate the switch to digital transactions due to the lack of infrastructure. 

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Disparity among in the preparedness for future 

The situation created by COVID-19 pandemic has provided important insights into the preparedness of various states to handle such a situation. Data indicates that few of the benefits (for e.g. younger population) might not sustain in the longer run unless structural changes are made to cope with the situation. On the other hand, states with better performance indicators (health faculties, per capita GSDP, Digital preparedness etc.) can mitigate an unfavourable situation (senior citizens, higher health risk etc.) and adjust according to changing situations faster than others. 

While indices at the national level like case positivity rate, fatality rate etc. point towards India doing better than many countries, a closer look at the data from various states indicate that the country has been fortunate to an extent with the distribution of the infection across the states. Higher infection in states with better facilities has helped in better handling of the situation. We could have had a potentially worse situation had the infection rate been higher in states with lesser preparedness. 

While the spread & control of the COVID-19 infection is an important aspect,  the recovery from the economic slowdown  is going to be equally important. COVID-19 has disrupted quite a few existing trends. It also exposed huge disparities among the states and any disruption like COVID-19 could impact the status quo. It is important that the country at in general & states in particular learn from this experience. 

Featured Image: COVID-19 impact on States


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HR professional, now focused on contributing towards a positive change in the society. Passionate reader. Loves writing and photography and to narrate stories through words and pictures.

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